S
Shingo Shimoda
Researcher at Toyota
Publications - 131
Citations - 880
Shingo Shimoda is an academic researcher from Toyota. The author has contributed to research in topics: Computer science & Medicine. The author has an hindex of 13, co-authored 111 publications receiving 669 citations. Previous affiliations of Shingo Shimoda include RIKEN Brain Science Institute.
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Journal ArticleDOI
Human-robot collaboration in precise positioning of a three-dimensional object
Tytus Wojtara,Masafumi Uchihara,Hideyuki Murayama,Shingo Shimoda,Satoshi Sakai,Hideo Fujimoto,Hidenori Kimura +6 more
TL;DR: This paper deals with fundamental issues of human-robot cooperation in precise positioning of a flat object on a target using in-house made robot prototype and several algorithms implementing these schemes are developed.
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A Synergetic Brain-Machine Interfacing Paradigm for Multi-DOF Robot Control
TL;DR: The user needs to only think about the end-point movement of the robot arm, which allows simultaneous multijoints control by BMI, and the support vector machine-based decoder designed in this paper is adaptive to the changing mental state of the user.
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Muscle synergy space: learning model to create an optimal muscle synergy
TL;DR: The results suggest that the CNS has the ability to create optimal sets of efficient behaviors by optimizing the size of the synergy space at the appropriate region through interacting with the environment.
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Temporal Features of Muscle Synergies in Sit-to-Stand Motion Reflect the Motor Impairment of Post-Stroke Patients
Ningjia Yang,Qi An,Hiroki Kogami,Hiroshi Yamakawa,Yusuke Tamura,Kouji Takahashi,Makoto Kinomoto,Hiroshi Yamasaki,Matti Itkonen,Fady Shibata-Alnajjar,Shingo Shimoda,Noriaki Hattori,Takanori Fujii,Hironori Otomune,Ichiro Miyai,Atsushi Yamashita,Hajime Asama +16 more
TL;DR: It is shown that temporal features in two muscle synergies that contribute to hip rising and balance maintenance motion reflect the motor impairment of post-stroke patients, which could lead to a new rehabilitation strategy for post- stroke patients that focuses on activation timing of muscle synergie.
Journal ArticleDOI
Biomimetic Approach to Tacit Learning Based on Compound Control
Shingo Shimoda,H. Kimura +1 more
TL;DR: It is shown that the individual activities of computational media can generate optimized behaviors from a particular global viewpoint, i.e., autonomous rhythm generation and learning of balanced postures, without using global performance indices.